WiMi Studies Hybrid Quantum-Classical Convolutional Neural Network Model

BEIJING, Oct. 23, 2025––WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global Hologram ...
Tech Xplore on MSN

VFF-Net algorithm provides promising alternative to backpropagation for AI training

Deep neural networks (DNNs), which power modern artificial intelligence (AI) models, are machine learning systems that learn ...
New Scientist

There's a simple way we could drastically cut AI energy use

If users chose the most efficient model each time they performed a task with AI, researchers calculate it would slash energy ...

MicroCloud Hologram Inc. Releases Hybrid Quantum-Classical Convolutional Neural Network, Achieving New Breakthrough in MNIST Multi-Class Classification

MicroCloud Hologram Inc. (NASDAQ: HOLO), (“HOLO” or the "Company"), a technology service provider, proposed a Quantum Convolutional Neural Network (QCNN) based on hybrid quantum-classical learning and ...
Semiconductor Engineering

Hybrid Approach Emerges For Edge/Cloud Inspection Of Chips

At the edge Models are built on the cloud and applied at the edge. Moving data from inspection/metrology systems to the cloud ...
Medical Design & Outsourcing

HOPPR releases EB 2D mammography foundation model for AI development

HOPPR Releases 2D Mammography Foundation Model to Accelerate AI Innovation in Breast Imaging New Vision Transformer-based ...
Unite.AI

DINOv3 and the Future of Computer Vision: Self-Supervised Learning at Scale

Labeling images is a costly and slow process in many computer vision projects. It often introduces bias and reduces the ability to scale large datasets. Therefore, researchers have been looking for ...
Medscape

AI Tool Advances Sjögren Disease Classification

A deep-learning artificial intelligence model trained on salivary gland biopsy images shows potential for classifying focus scores and Sjögren disease.
TMCnet

SEOULTECH Researchers Develop VFF-Net, A Revolutionary Alternative to Backpropagation That Transforms AI Training

While it has become indispensable for the success of DNNs, BP has several limitations, such as slow convergence, overfitting, high computational requirements, and its black box nature. Recently, ...